Diagnosis of Chronic Kidney Disease Using Effective Classification Algorithms and Recursive Feature Elimination Techniques

Table 8

Comparison of the performance of our proposed system with previous studies.

Previous studies	Accuracy %	Precision %	Recall %	F1-score %
Hore et al. [29]	92.54	85.71	96	90.56
Vasquez-Morales et al. [11]	92	93	90	91
Rady and Anwar [13]	95.84	84.06	93.55	88.55
Elhoseny et al. [19]	85		88	88
Ogunleye and Wang [30]	96.8		87	93
Khan et al. [31]	95.75	96.2	95.8	95.8
Chittora et al. [32]	90.73	83.34	93	88.05
Jongbo et al. [33]	89.2	97.72	97.8
Harimoorthy and Thangavelu [34]	66.3	65.9	65.9
Proposed model (random forest)	100	100	100	100
Proposed model (decision tree)	99.34	98.68	100	99.17
Proposed model (KNN)	98.33	100	97.37	98.67
Proposed model (SVM)	97.3	94.74	92	96.67